Modified Mahalanobis Taguchi System for Imbalance Data Classification

المؤلف

El-Banna, Mahmoud

المصدر

Computational Intelligence and Neuroscience

العدد

المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-15، 15ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2017-07-24

دولة النشر

مصر

عدد الصفحات

15

التخصصات الرئيسية

الأحياء

الملخص EN

The Mahalanobis Taguchi System (MTS) is considered one of the most promising binary classification algorithms to handle imbalance data.

Unfortunately, MTS lacks a method for determining an efficient threshold for the binary classification.

In this paper, a nonlinear optimization model is formulated based on minimizing the distance between MTS Receiver Operating Characteristics (ROC) curve and the theoretical optimal point named Modified Mahalanobis Taguchi System (MMTS).

To validate the MMTS classification efficacy, it has been benchmarked with Support Vector Machines (SVMs), Naive Bayes (NB), Probabilistic Mahalanobis Taguchi Systems (PTM), Synthetic Minority Oversampling Technique (SMOTE), Adaptive Conformal Transformation (ACT), Kernel Boundary Alignment (KBA), Hidden Naive Bayes (HNB), and other improved Naive Bayes algorithms.

MMTS outperforms the benchmarked algorithms especially when the imbalance ratio is greater than 400.

A real life case study on manufacturing sector is used to demonstrate the applicability of the proposed model and to compare its performance with Mahalanobis Genetic Algorithm (MGA).

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

El-Banna, Mahmoud. 2017. Modified Mahalanobis Taguchi System for Imbalance Data Classification. Computational Intelligence and Neuroscience،Vol. 2017, no. 2017, pp.1-15.
https://search.emarefa.net/detail/BIM-1141027

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

El-Banna, Mahmoud. Modified Mahalanobis Taguchi System for Imbalance Data Classification. Computational Intelligence and Neuroscience No. 2017 (2017), pp.1-15.
https://search.emarefa.net/detail/BIM-1141027

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

El-Banna, Mahmoud. Modified Mahalanobis Taguchi System for Imbalance Data Classification. Computational Intelligence and Neuroscience. 2017. Vol. 2017, no. 2017, pp.1-15.
https://search.emarefa.net/detail/BIM-1141027

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1141027